A novel method to assess short-term forest cover changes based on digital surface models from image-based point clouds

Assessing forest cover change is a key issue for any national forest inventory. This was tested in two study areas in Switzerland on the basis of stereo airborne digital sensor (ADS) images and advanced digital surface model (DSM) generation techniques based on image point clouds. In the present study, an adaptive multi-scale approach to detect forest cover change with high spatial and temporal resolution was applied to two study areas in Switzerland. The challenge of this approach is to minimize DSM height uncertainties that may affect the accuracy of the forest cover change results. The approach consisted of two steps. In the first step, a ‘change index' parameter indicated the overall change status at a coarser scale. The tendency towards change was indicated by derivative analysis of the normalized histograms of the difference between the two canopy height models (DCHMs) in different years. In the second step, detection of forest cover change at a refined scale was based on an automatic threshold and a moving window technique. Promising results were obtained and reveal that real forest cover changes can be distinguished from non-changes with a high degree of accuracy in managed mixed forests. Results had a lower accuracy for forests located on steep alpine terrain. A major benefit of the proposed method is that the magnitude of forest cover change of any specific region can be made available within a short time as often required by forest managers or policy-makers, especially after unexpected natural disturbance

Countrywide mapping of shrub forest using multi-sensor data and bias correction techniques

The continual increase of shrub forest in the Swiss Alps over the past few decades impacts biodiversity, forest succession and the protective function of forests. Therefore, up-to-date and area-wide information on its distribution is of great interest. To detect the shrub forest areas for the whole of Switzerland (41,285 km2), we developed an approach that uses Random Forest (RF), bias correction techniques and data from multiple remote sensing sources. Manual aerial orthoimage interpretation of shrub forest areas was conducted in a non-probabilistic way to derive initial training data. The multi-sensor and open access predictor data included digital terrain and vegetation height models obtained from Airborne Laser Scanning (ALS) and stereo-imagery, as well as Synthetic Aperture Radar (SAR) backscatter from Sentinel-1 and multispectral imagery from Sentinel-2. To mitigate the expected bias due to the training data sampling strategy, two techniques using RF probability estimates were tested to improve mapping accuracy. 1) an iterative and semi-automated active learning technique was used to generate further training data and 2) threshold-moving related object growing was applied. Both techniques facilitated the production of a shrub forest map for the whole of Switzerland at a spatial resolution of 10 m. An accuracy assessment was performed using independent data covering 7640 regularly distributed National Forest Inventory (NFI) plots. We observed the influence of the bias correction techniques and found higher accuracies after each performed iteration. The Mean Absolute Error (MAE) for the predicted shrub forest proportion was reduced from 6.04% to 2.68% while achieving a Mean Bias Error (MBE) of close to 0. The present study underscores the potential of combining multi-sensor data with bias correction techniques to provide cost-effective and accurate countrywide detection of shrub forest. Moreover, the map complements currently available NFI plot sample point data

Driving factors of a vegetation shift from Scots pine to pubescent oak in dry Alpine forests

An increasing number of studies have reported on forest declines and vegetation shifts triggered by drought. In the Swiss Rhone valley (Valais), one of the driest inner-Alpine regions, the species composition in low elevation forests is changing: The sub-boreal Scots pine (Pinus sylvestris L.) dominating the dry forests is showing high mortality rates. Concurrently the sub-Mediterranean pubescent oak (Quercus pubescens Willd.) has locally increased in abundance. However, it remains unclear whether this local change in species composition is part of a larger-scale vegetation shift. To study variability in mortality and regeneration in these dry forests we analysed data from the Swiss national forest inventory (NFI) on a regular grid between 1983 and 2003, and combined it with annual mortality data from a monitoring site. Pine mortality was found to be highest at low elevation (below 1000 m a.s.l.). Annual variation in pine mortality was correlated with a drought index computed for the summer months prior to observed tree death. A generalized linear mixed-effects model indicated for the NFI data increased pine mortality on dryer sites with high stand competition, particularly for small-diameter trees. Pine regeneration was low in comparison to its occurrence in the overstorey, whereas oak regeneration was comparably abundant. Although both species regenerated well at dry sites, pine regeneration was favoured at cooler sites at higher altitude and oak regeneration was more frequent at warmer sites, indicating a higher adaptation potential of oaks under future warming. Our results thus suggest that an extended shift in species composition is actually occurring in the pine forests in the Valais. The main driving factors are found to be climatic variability, particularly drought, and variability in stand structure and topography. Thus, pine forests at low elevations are developing into oak forests with unknown consequences for these ecosystems and their goods and services

Long-term soil water limitation and previous tree vigor drive local variability of drought-induced crown dieback in Fagus sylvatica.

Ongoing climate warming is increasing evapotranspiration, a process that reduces plant-available water and aggravates the impact of extreme droughts during the growing season. Such an exceptional hot drought occurred in Central Europe in 2018 and caused widespread defoliation in mid-summer in European beech (Fagus sylvatica L.) forests. Here, we recorded crown damage in 2021 in nine mature even-aged beech-dominated stands in northwestern Switzerland along a crown damage severity gradient (low, medium, high) and analyzed tree-ring widths of 21 mature trees per stand. We aimed at identifying predisposing factors responsible for differences in crown damage across and within stands such as tree growth characteristics (average growth rates and year-to-year variability) and site-level variables (mean canopy height, soil properties). We found that stand-level crown damage severity was strongly related to soil water availability, inferred from tree canopy height and plant available soil water storage capacity (AWC). Trees were shorter in drier stands, had higher year-to-year variability in radial growth, and showed higher growth sensitivity to moisture conditions of previous late summer than trees growing on soils with sufficient AWC, indicating that radial growth in these forests is principally limited by soil water availability. Within-stand variation of post-drought crown damage corresponded to growth rate and tree size (diameter at breast height, DBH), i.e., smaller and slower-growing trees that face more competition, were associated with increased crown damage after the 2018 drought. These findings point to tree vigor before the extreme 2018 drought (long-term relative growth rate) as an important driver of damage severity within and across stands. Our results suggest that European beech is less likely to be able to cope with future climate change-induced extreme droughts on shallow soils with limited water retention capacity

Prevalence of concomitant rheumatologic diseases and autoantibody specificities among racial and ethnic groups in SLE patients

Objective: Leveraging the Manhattan Lupus Surveillance Program (MLSP), a population-based registry of cases of systemic lupus erythematosus (SLE) and related diseases, we investigated the proportion of SLE with concomitant rheumatic diseases, including Sjögren’s disease (SjD), antiphospholipid syndrome (APLS), and fibromyalgia (FM), as well as the prevalence of autoantibodies in SLE by sex and race/ethnicity. Methods: Prevalent SLE cases fulfilled one of three sets of classification criteria. Additional rheumatic diseases were defined using modified criteria based on data available in the MLSP: SjD (anti-SSA/Ro positive and evidence of keratoconjunctivitis sicca and/or xerostomia), APLS (antiphospholipid antibody positive and evidence of a blood clot), and FM (diagnosis in the chart). Results: 1,342 patients fulfilled SLE classification criteria. Of these, SjD was identified in 147 (11.0%, 95% CI 9.2–12.7%) patients with women and non-Latino Asian patients being the most highly represented. APLS was diagnosed in 119 (8.9%, 95% CI 7.3–10.5%) patients with the highest frequency in Latino patients. FM was present in 120 (8.9%, 95% CI 7.3–10.5) patients with non-Latino White and Latino patients having the highest frequency. Anti-dsDNA antibodies were most prevalent in non-Latino Asian, Black, and Latino patients while anti-Sm antibodies showed the highest proportion in non-Latino Black and Asian patients. Anti-SSA/Ro and anti-SSB/La antibodies were most prevalent in non-Latino Asian patients and least prevalent in non-Latino White patients. Men were more likely to be anti-Sm positive. Conclusion: Data from the MLSP revealed differences among patients classified as SLE in the prevalence of concomitant rheumatic diseases and autoantibody profiles by sex and race/ethnicity underscoring comorbidities associated with SLE

Breast cancer in systemic lupus

OBJECTIVE: There is a decreased breast cancer risk in systemic lupus erythematosus (SLE) versus the general population. We assessed a large sample of SLE patients, evaluating demographic and clinical characteristics and breast cancer risk. METHODS: We performed case-cohort analyses within a multi-center international SLE sample. We calculated the breast cancer hazard ratio (HR) in female SLE patients, relative to demographics, reproductive history, family history of breast cancer, and time-dependent measures of anti-dsDNA positivity, cumulative disease activity, and drugs, adjusted for SLE duration. RESULTS: There were 86 SLE breast cancers and 4498 female SLE cancer-free controls. Patients were followed on average for 7.6 years. Versus controls, SLE breast cancer cases tended to be white and older. Breast cancer cases were similar to controls regarding anti-dsDNA positivity, disease activity, and most drug exposures over time. In univariate and multivariate models, the principal factor associated with breast cancers was older age at cohort entry. CONCLUSIONS: There was little evidence that breast cancer risk in this SLE sample was strongly driven by any of the clinical factors that we studied. Further search for factors that determine the lower risk of breast cancer in SLE may be warranted

Anti-beta 2 glycoprotein I IgA in the SLICC classification criteria dataset

OBJECTIVE: Anti-beta 2 glycoprotein I IgA is a common isotype of anti-beta 2 glycoprotein I in SLE. Anti-beta 2 glycoprotein I was not included in the American College of Rheumatology (ACR) SLE classification criteria, but was included in the Systemic Lupus International Collaborating Clinics (SLICC) criteria. We aimed to evaluate the prevalence of anti-beta 2-glycoprotein I IgA in SLE versus other rheumatic diseases. In addition, we examined the association between anti-beta 2 glycoprotein I IgA and disease manifestations in SLE. METHODS: The dataset consisted of 1384 patients, 657 with a consensus physician diagnosis of SLE and 727 controls with other rheumatic diseases. Anti-beta 2 glycoprotein I isotypes were measured by ELISA. Patients with a consensus diagnosis of SLE were compared to controls with respect to presence of anti-beta 2 glycoprotein I. Among patients with SLE, we assessed the association between anti-beta 2 glycoprotein I IgA and clinical manifestations. RESULTS: The prevalence of anti-beta 2 glycoprotein I IgA was 14% in SLE patients and 7% in rheumatic disease controls (odds ratio, OR 2.3, 95% CI: 1.6, 3.3). It was more common in SLE patients who were younger patients and of African descent (p = 0.019). Eleven percent of SLE patients had anti-beta 2 glycoprotein I IgA alone (no anti-beta 2 glycoprotein I IgG or IgM). There was a significant association between anti-beta 2 glycoprotein I IgA and anti-dsDNA (p = 0.001) and the other antiphospholipid antibodies (p = 0.0004). There was no significant correlation of anti-beta 2 glycoprotein I IgA with any of the other ACR or SLICC clinical criteria for SLE. Those with anti-beta 2 glycoprotein I IgA tended to have a history of thrombosis (12% vs 6%, p = 0.071), but the difference was not statistically significant. CONCLUSION: We found the anti-beta 2 glycoprotein I IgA isotype to be more common in patients with SLE and in particular, with African descent. It could occur alone without other isotypes